Big (Bio)Chemical Data Mining Using Chemometric Methods: A Need for Chemists.

Autor: Parastar, Hadi; Tauler, Roma

Publication year: 2022

Angewandte Chemie (International ed. in English)

issn:1521-3773 1433-7851

doi: 10.1002/anie.201801134

Abstract:

This Review summarizes how big (bio)chemical data (BBCD) can be analyzed with multivariate chemometric methods and highlights some of the important challenges faced by modern analytical researches. Here, the potential of chemometric methods to solve BBCD problems that are being encountered in chromatographic, spectroscopic and hyperspectral imaging measurements will be discussed, with an emphasis on their applications to omics sciences. In addition, insights and perspectives on how to address the analysis of BBCD are provided along with a discussion of the procedures necessary to obtain more reliable qualitative and quantitative results. In this Review, the importance of “big data” and of their relevance to (bio)chemistry are first discussed. Thereafter, analytical tools which can produce BBCD are presented as well as the theoretical background of chemometric methods and their limitations when they are applied to BBCD. Finally, the importance of chemometric methods for the analysis of BBCD in different chemical disciplines is highlighted with some examples. In this work, we have tried to cover many of the current applications of big data analysis in the (bio)chemistry field.

Language: eng

Pmid: 29569816

Tags: *Chemometrics; *Data Mining; Big Data; Chemometrics; Chromatography; Mass Spectrometry; Omics Science; Spectrum Analysis

Link: https://pubmed.ncbi.nlm.nih.gov/29569816/